Association between mental health, caries experience and gingival health of adolescents in sub-urban Nigeria
Bibliographic record
Abstract
BACKGROUND: This study assessed the association of mental health problems and risk indicators of mental health problems with caries experience and moderate/severe gingivitis in adolescents. METHODS: A cross-sectional household survey was conducted in Osun State, Nigeria. Data collected from 10 to 19-years-old adolescents between December 2018 and January 2019 were sociodemographic variables (age, sex, socioeconomic status); oral health indicators (tooth brushing, use of fluoridated toothpaste, consumption of refined carbohydrates in-between-meals, dental services utilization, dental anxiety and plaque); mental health indicators (smoking habits, intake of alcohol and use of psychoactive drugs) and mental health problems (low and high). Gingival health (healthy gingiva/mild gingivitis versus moderate/severe gingivitis) and caries experience (present or absent) were also assessed. A series of five logistic regression models were constructed to determine the association between presence of caries experience and presence of moderate/severe gingivitis) with blocks of independent variables. The blocks were: model 1-sociodemographic factors; model 2-oral health indicators; model 3-mental health indicators and model 4-mental health problems. Model 5 included all factors from models 1 to 4. RESULTS: There were 1234 adolescents with a mean (SD) age of 14.6 (2.7) years. Also, 21.1% of participants had high risk of mental health problems, 3.7% had caries experience, and 8.1% had moderate/severe gingivitis. Model 5 had the best fit for the two dependent variables. The use of psychoactive substances (AOR 2.67; 95% CI 1.14, 6.26) was associated with significantly higher odds of caries experience. The frequent consumption of refined carbohydrates in-between-meals (AOR: 0.41; 95% CI 0.25, 0.66) and severe dental anxiety (AOR0.48; 95% CI 0.23, 0.99) were associated with significantly lower odds of moderate/severe gingivitis. Plaque was associated with significant higher odds of moderate/severe gingivitis (AOR 13.50; 95% CI 8.66, 21.04). High risk of mental health problems was not significantly associated with caries experience (AOR 1.84; 95% CI 0.97, 3.49) or moderate/severe gingivitis (AOR 0.80; 95% CI 0.45, 1.44). CONCLUSION: The association between mental problems and risk indicators with oral diseases in Nigerian adolescents indicates a need for integrated mental and oral health care to improve the wellbeing of adolescents.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".